The availability of commodity depth cameras and sensors such as Microsoft Corporation's Kinect® have enabled the development of methods which can densely reconstruct arbitrary scenes from captured depth images. The task of generating dense 3D reconstructions of scenes from depth images has seen great progress in the last few years. While part of this progress is due to algorithmic improvements, large strides have been made with the adoption of inexpensive depth cameras and the fusion of color and depth signals.
The combined use of depth and color images has been successfully demonstrated for the production of large-scale models of indoor scenes via both offline and online algorithms. Most red, green, blue and depth (RGB+D) reconstruction methods require data that show the scene from a multitude of viewpoints to provide a substantially accurate and complete surface reconstruction.
Accurate and complete surface reconstruction is of special importance in Augmented Reality (AR) applications which are increasingly being used for both entertainment and commercial purposes. For example, a recently introduced gaming platform asks users to scan an interior scene from multiple angles to construct a model of the scene. Using the densely reconstructed model, the platform overlays graphically generated characters and gaming elements. In another example, furniture retailers can enable customers to visualize how their furniture will look when installed without having to leave their homes. These AR applications often require a high fidelity dense reconstruction so that simulated physical phenomenon, such as lighting, shadow and object interactions can be produced in a plausible fashion.